This study employs the perspective of social exchange theory and seeks to understand users' intentions to use social recommender systems (SRS) through three psychological factors: trust, shared values, and reputation. We use structural equation modeling to analyze 221 valid questionnaires. The results show that trust has a direct positive influence on the intention to use SRS, followed by shared values, whereas reputation has an indirect influence on SRS use. We further discuss specific recommendations concerning these factors for developing SRS.
Get full access to this article
View all access options for this article.
References
1.
AnsariA, EssegaierS, KohliR. Internet recommendation systems. Journal of Marketing Research, 2000; 37:363–375.
2.
SenecalS, KalczynskiPJ, NantelJ. Consumers' decision-making process and their online shopping behavior: a clickstream analysis. Journal of Business Research, 2005; 58:1599–1608.
3.
GnyawaliDR, FanW, PennerJ. Competitive actions and dynamics in the digital age: an empirical investigation of social networking firms. Information Systems Research, 2010; 21:594–613.
4.
WirtzBW, SchilkeO, UllrichS. Strategic development of business models: implications of the web 2.0 for creating value on the Internet. Long Range Planning, 2010; 43:272–290.
5.
HungCL, ChouJCL, DongTP. Innovations and communication through innovative users: an exploratory mechanism of social networking website. International Journal of Information Management, 2011; 31:317–326.
6.
XiaoB, BenbasatI. E-commerce product recommendation agents: use, characteristics, and impact. MIS Quarterly, 2007; 31:137–209.
7.
PathakB, GarfinkelR, GopalRDet al.Empirical analysis of the impact of recommender systems on sales. Journal of Management Information Systems, 2010; 27:159–188.
8.
LuoX. Trust production and privacy concerns on the Internet: a framework based on relationship marketing and social exchange theory. Industrial Marketing Management, 2002; 31:111–118.
9.
MuthusamySK, WhiteMA. Learning and knowledge transfer in strategic alliances: a social exchange view. Organization Studies, 2005; 26:415–441.
10.
ChenZ, LamW, ZhongJA. Leader-member exchange and member performance: a new look at individual-level negative feedback-seeking behavior and team-level empowerment climate. Journal of Applied Psychology, 2007; 92:202–212.
11.
HsuCL, LinJCC. Acceptance of blog usage: the roles of technology acceptance, social influence and knowledge sharing motivation. Information and Management, 2008; 45:65–74.
12.
FreemanLC. Centrality in social networks conceptual clarification. Social Networks, 1979; 1:215–239.
13.
UeharaE. Dual exchange theory, social networks, and informal social support. American Journal of Sociology, 1990; 96:521–557.
14.
BoydDM, EllisonNB. Social network sites: definition, history, and scholarship. Journal of Computer-Mediated Communication, 2007; 13:210–230.
15.
GuyI, CarmelD. 2011. Social recommender systems. Proceedings of the 20th International Conference Companion on World Wide Web. New York, NY, Association of Computing Machinery.
16.
BonhardP, SasseMA. ‘Knowing me, knowing you’—using profiles and social networking to improve recommender systems. BT Technology Journal, 2006; 24:84–98.
17.
ArazyO, KumarN, ShapiraB. A theory-driven design framework for social recommender systems. Journal of the Association for Information Systems, 2010; 11:455–490.
18.
GrohG, BirnkammererS, KöllhoferV. 2012. Social recommender systems. AriasJJP, VilasAF, RedondoRPD. Recommender systems for the social web. Intelligent Systems Reference Library: Berlin: Springer. 32:3–42.
19.
TutkuteL, ButlerisR, SkersysT. An approach for the formation of leverage coefficients-based recommendations in social network. Information Technology and Control, 2008; 37:245–254.
20.
RafaeliS, Dan-GurY, BarakM. Social recommender systems: recommendations in support of e-learning. International Journal of Distance Education Technologies, 2005; 3:29–45.
21.
LeeJ, ParkDH, HanI. The effect of negative online consumer reviews on product attitude: an information processing view. Electronic Commerce Research and Applications, 2008; 7:341–352.
22.
JeongE, JangS. Restaurant experiences triggering positive electronic word-of-mouth (eWOM) motivations. International Journal of Hospitality Management, 2011; 30:356–366.
23.
LiJ, LeeA, LiuJ. 2011. Are these reviews for real? The importance of belief and trust in reviews and word-of-mouth for web-purchases. Proceedings of the 8th International Conference on Service Systems and Service Management (ICSSSM)Tianjin, China, IEEE, 25–27.
24.
ZhangJQ, CraciunG, ShinD. When does electronic word-of-mouth matter? A study of consumer product reviews. Journal of Business Research, 2010; 63:1336–1341.
25.
LinYC. 2011. The impacts of information technology enabled services on service innovations: a case study in a publishing company. Proceedings of the Services Computing Conference (APSCC)Jeju Island, Korea, IEEE Asia-Pacific, 41–47.
26.
KimJ, LaRoseR, PengW. Loneliness as the cause and the effect of problematic Internet use: the relationship between Internet use and psychological well-being. CyberPsychology and Behavior, 2009; 12:451–455.
27.
BlauJS. 1964. Exchange and power in social life. New York: Wiley.
28.
ChenYH, ChienSH, WuJJet al.Impact of signals and experience on trust and trusting behavior. Cyberpsychology, Behavior, and Social Networking, 2010; 13:539–546.
29.
Grabner-KräuterS. Web 2.0 social networks: the role of trust. Journal of Business Ethics, 2009; 90:505–522.
30.
WangW, BenbasatI. Recommendation agents for electronic commerce: effects of explanation facilities on trusting beliefs. Journal of Management Information Systems, 2007; 23:217–246.
31.
ChowWS, ChanLS. Social network, social trust and shared goals in organizational knowledge sharing. Information and Management, 2008; 45:458–465.
32.
ChuSC, ChoiSM. Electronic word-of-mouth in social networking sites: a cross-cultural study of the United States and China. Journal of Global Marketing, 2011; 24:263–281.
33.
LinKY, LuHP. Intention to continue using Facebook fan pages from the perspective of social capital theory. Cyberpsychology, Behavior, and Social Networking, 2011; 14:565–570.
34.
Young-YbarraC, WiersemaM. Strategic flexibility in information technology alliances: the influence of transaction cost economics and social exchange theory. Organization Science, 1999; 10–439,459.
35.
JøsangA, IsmailR, BoydC. A survey of trust and reputation systems for online service provision. Decision Support Systems, 2007; 43:618–644.
36.
JohnsonD, GraysonK. Cognitive and affective trust in service relationships. Journal of Business Research, 2005; 58:500–507.
37.
KoufarisM, Hampton-SosaW. The development of initial trust in an online company by new customers. Information and Management, 2004; 41:377–397.
38.
KimDJ, FerrinDL, RaoHR. A trust-based consumer decision-making model in electronic commerce: the role of trust, perceived risk, and their antecedents. Decision Support Systems, 2008; 44:544–564.
39.
AksoyL, BuoyeA, CooilBet al.Can we talk? The impact of willingness to recommend on a new-to-market service brand extension within a social network. Journal of Service Research, 2011; 14:355–371.
40.
McClungS, JohnsonK. Examining the motives of podcast users. Journal of Radio and Audio Media, 2010; 17:82–95.
41.
RensnickP, ZeckhauserR, SwansonJet al.The value of reputation on eBay: a controlled experiment. Experimental Economics, 2006; 9:79–101.
42.
DiniF, SpagnoloG. Buying reputation on eBay: do recent changes help?International Journal of Electronic Business, 2009; 7:581–598.
43.
SwamynathanG, AlmerothKC, ZhaoBY. The design of a reliable reputation system. Electronic Commerce Research, 2010; 10:239–270.
44.
CasalóLV, FlaviánC, GuinalíuM. The role of security, privacy, usability and reputation in the development of online banking. Online Information Review, 2007; 31:583–603.
45.
CheemaA. Surcharges and seller reputation. Journal of Consumer Research, 2008; 35:167–177.
46.
WangW, ZengG, YuanL. 2006. A semantic reputation mechanism in P2P semantic web. Proceedings of the First Asian Semantic Web Conference (ASWC)Beijing, China, Lecture Notes in Computer Science. 4185:682–688.
47.
GuptaP, HarrisJ. How e-WOM recommendations influence product consideration and quality of choice: a motivation to process information perspective. Journal of Business Research, 2010; 63:1041–1049.
48.
MathwickC. Understanding the online consumer: a typology of online relational norms and behavior. Journal of Interactive Marketing, 2002; 16:40–55.
49.
EmlerN. A social psychology of reputation. European Review of Social Psychology, 1990; 1:171–193.
50.
KrackhardtD, KilduffM. Whether close or far: social distance effects on perceived balance in friendship networks. Journal of Personality and Social Psychology, 1999; 76:770–782.
51.
MukherjeeA, NathP. Role of electronic trust in online retailing: a re-examination of the commitment-trust theory. European Journal of Marketing, 2007; 41:1173–1202.
52.
WaskoMM, FarajS. Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly, 2005; 29:35–57.
53.
CryD, HassaneinK, HeadMet al.The role of social presence in establishing loyalty in e-Service environments. Interacting with Computers, 2007; 19:43–56.
54.
CohenD, PrusakL. 2001. In good company: how social capital makes organizations work. Boston, MA: Harvard Business School Press.
55.
BélangerF, CarterL. Trust and risk in e-government adoption. Journal of Strategic Information Systems, 2008; 17:165–176.
56.
FornellC, LarckerDF. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 1981; 18:39–50.
57.
BagozziRP, YiY. On the evaluation of structural equation models. Journal of Academy of Marketing Science, 1988; 16:74–94.
58.
HairJF, AndersonRE, TathamRLet al.1998. Multivariate data analysis. London: Prentice Hall.
59.
HungSY, LaiHM, ChangWW. Knowledge-sharing motivations affecting R&D employees' acceptance of electronic knowledge repository. Behaviour and Information Technology, 2011; 30:213–230.
60.
SulerJ. The online disinhibition effect. CyberPsychology and Behavior, 2004; 7:321–326.
61.
ZhangLF, ZhangFJ. Does e-commerce reputation mechanism matter?Procedia Engineering, 2011; 15:4885–4889.
62.
MascletD, PénardT. Do reputation feedback systems really improve trust among anonymous traders? An experimental study. Applied Economics, 2012; 44:4553–4573.
